{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cyber Threat Hunting - Chapter 6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scenario"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ACQUIRE AND PREPARE DATA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28f291d7-2dc7-410d-8272-4db70cbf53f4",
   "metadata": {},
   "source": [
    "### Listing 6.7 Jupyter notebook – Collect events a local csv file\n",
    "\n",
    "- A Import the pandas library into the Python program and aliases it as pd\n",
    "- B Read a CSV file named ch6_stream_events.csv into pandas DataFrame, df. A The low_memory=False parameter is used to minimize memory usage while reading the file. This is useful for large files or when the data types in the columns are mixed.\n",
    "- C Print the length of DataFrame df\n",
    "- D Copy df_original to a new a dataframe, df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "667827\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df_original = pd.read_csv(\"/Users/nalfarda/Documents/Work/SA/Books/Hunting Book/Proposal/Manning/Book Writing/Chapter 6/Data/output.csv\", low_memory=False)\n",
    "print(len(df_original))\n",
    "df = df_original"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c692cc1-cf83-4748-af77-cf967f9aec0b",
   "metadata": {},
   "source": [
    "#### Listing 6.8 Jupyter notebook code – Filter events based on a count threshold\n",
    "\n",
    "- A Set the value of variable count_threshold to 100\n",
    "- B Keep events that share the same src_ip, dest_ip, and dest_port if the total count > count_threshold\n",
    "- C reset_index() takes the current index, and places it in column 'index'. Then it recreates a new 'linear' index for the dataset\n",
    "- D Print the number of rows in DataFrame df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "897fe203-79f0-4401-88eb-2d7a63af118b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "511346 records with count > 100\n"
     ]
    }
   ],
   "source": [
    "count_threshold = 100\n",
    "df = df.groupby(['src_ip', 'dest_ip', 'dest_port']).filter \\\n",
    "    (lambda x : len(x)>count_threshold)\n",
    "df = df.reset_index()\n",
    "print(len(df.index), \"records with count >\", count_threshold)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.9 Jupyter notebook – Data type of each column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3aafe43c-4f30-4e66-ab0f-609138e68323",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "index               int64\n",
       "Unnamed: 0          int64\n",
       "sourcetype         object\n",
       "endtime            object\n",
       "timestamp          object\n",
       "                   ...   \n",
       "uri_parm           object\n",
       "message_type       object\n",
       "query              object\n",
       "query_type         object\n",
       "transaction_id    float64\n",
       "Length: 79, dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.11 Jupyter notebook code – Calculate the epoch of timestamp and endtime\n",
    "- A Convert the timestamp column to datetime object, accommodating mixed formats.\n",
    "- B Convert the endtime column to datetime object, accommodating mixed formats.\n",
    "- C Transform timestamp object to epoch timestamps (seconds since Jan 1, 1970) and store it in new columns epoch_timestamp.\n",
    "- D Transform endtime object to epoch timestamps (seconds since Jan 1, 1970) and store it in new column epoch_endtime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['timestamp'] = pd.to_datetime(df['timestamp'], format='mixed')\n",
    "df['endtime'] = pd.to_datetime(df['endtime'], format='mixed')\n",
    "df['epoch_timestamp'] = df['timestamp'].astype('int64') // 10**9\n",
    "df['epoch_endtime'] = df['endtime'].astype('int64') // 10**9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the data/time to epoch conversion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>epoch_timestamp</th>\n",
       "      <th>endtime</th>\n",
       "      <th>epoch_endtime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-07-27 14:46:54.346452+00:00</td>\n",
       "      <td>1658933214</td>\n",
       "      <td>2022-07-27 14:46:54.346488+00:00</td>\n",
       "      <td>1658933214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-07-27 14:46:53.839881+00:00</td>\n",
       "      <td>1658933213</td>\n",
       "      <td>2022-07-27 14:46:53.839898+00:00</td>\n",
       "      <td>1658933213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-07-27 14:46:53.332432+00:00</td>\n",
       "      <td>1658933213</td>\n",
       "      <td>2022-07-27 14:46:53.332470+00:00</td>\n",
       "      <td>1658933213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-07-27 14:46:52.595835+00:00</td>\n",
       "      <td>1658933212</td>\n",
       "      <td>2022-07-27 14:46:53.566740+00:00</td>\n",
       "      <td>1658933213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-07-27 14:46:52.682650+00:00</td>\n",
       "      <td>1658933212</td>\n",
       "      <td>2022-07-27 14:46:53.565587+00:00</td>\n",
       "      <td>1658933213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511341</th>\n",
       "      <td>2022-07-27 14:13:21.350702+00:00</td>\n",
       "      <td>1658931201</td>\n",
       "      <td>2022-07-27 14:13:21.806954+00:00</td>\n",
       "      <td>1658931201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511342</th>\n",
       "      <td>2022-07-27 14:13:21.121610+00:00</td>\n",
       "      <td>1658931201</td>\n",
       "      <td>2022-07-27 14:13:21.124701+00:00</td>\n",
       "      <td>1658931201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511343</th>\n",
       "      <td>2022-07-27 14:13:11.289744+00:00</td>\n",
       "      <td>1658931191</td>\n",
       "      <td>2022-07-27 14:13:11.290784+00:00</td>\n",
       "      <td>1658931191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511344</th>\n",
       "      <td>2022-07-27 14:13:21.122611+00:00</td>\n",
       "      <td>1658931201</td>\n",
       "      <td>2022-07-27 14:13:21.124279+00:00</td>\n",
       "      <td>1658931201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511345</th>\n",
       "      <td>2022-07-27 14:13:20.704115+00:00</td>\n",
       "      <td>1658931200</td>\n",
       "      <td>2022-07-27 14:13:20.766733+00:00</td>\n",
       "      <td>1658931200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>511346 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              timestamp  epoch_timestamp  \\\n",
       "0      2022-07-27 14:46:54.346452+00:00       1658933214   \n",
       "1      2022-07-27 14:46:53.839881+00:00       1658933213   \n",
       "2      2022-07-27 14:46:53.332432+00:00       1658933213   \n",
       "3      2022-07-27 14:46:52.595835+00:00       1658933212   \n",
       "4      2022-07-27 14:46:52.682650+00:00       1658933212   \n",
       "...                                 ...              ...   \n",
       "511341 2022-07-27 14:13:21.350702+00:00       1658931201   \n",
       "511342 2022-07-27 14:13:21.121610+00:00       1658931201   \n",
       "511343 2022-07-27 14:13:11.289744+00:00       1658931191   \n",
       "511344 2022-07-27 14:13:21.122611+00:00       1658931201   \n",
       "511345 2022-07-27 14:13:20.704115+00:00       1658931200   \n",
       "\n",
       "                                endtime  epoch_endtime  \n",
       "0      2022-07-27 14:46:54.346488+00:00     1658933214  \n",
       "1      2022-07-27 14:46:53.839898+00:00     1658933213  \n",
       "2      2022-07-27 14:46:53.332470+00:00     1658933213  \n",
       "3      2022-07-27 14:46:53.566740+00:00     1658933213  \n",
       "4      2022-07-27 14:46:53.565587+00:00     1658933213  \n",
       "...                                 ...            ...  \n",
       "511341 2022-07-27 14:13:21.806954+00:00     1658931201  \n",
       "511342 2022-07-27 14:13:21.124701+00:00     1658931201  \n",
       "511343 2022-07-27 14:13:11.290784+00:00     1658931191  \n",
       "511344 2022-07-27 14:13:21.124279+00:00     1658931201  \n",
       "511345 2022-07-27 14:13:20.766733+00:00     1658931200  \n",
       "\n",
       "[511346 rows x 4 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['timestamp', 'epoch_timestamp', 'endtime', 'epoch_endtime']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.12 Jupyter notebook code – Convert columns of type of object to type integer\n",
    "Convert the fields that contain numeric values to type integer, `int`, so that we can run our calcualtions later.\n",
    "\n",
    "- A Convert the values in the column epoch_timestamp of the DataFrame df df integers.\n",
    "- B Convert the values in the column epoch_endtime of the DataFrame df to integers.\n",
    "- C Convert the values in the column bytes of the DataFrame df to integers.\n",
    "- D Convert the values in the column bytes_in of the DataFrame df to integers.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "766bd624-028c-4900-adde-3f4a0ed4f1af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "index                            int64\n",
       "Unnamed: 0                       int64\n",
       "sourcetype                      object\n",
       "endtime            datetime64[ns, UTC]\n",
       "timestamp          datetime64[ns, UTC]\n",
       "                          ...         \n",
       "query                           object\n",
       "query_type                      object\n",
       "transaction_id                 float64\n",
       "epoch_timestamp                  int64\n",
       "epoch_endtime                    int64\n",
       "Length: 81, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.sort_values(by=['epoch_timestamp'], ascending=True)\n",
    "df['epoch_timestamp'] = df['epoch_timestamp'].astype(int)\n",
    "df['epoch_endtime'] = df['epoch_endtime'].astype(int)\n",
    "df['bytes'] = df['bytes'].astype(int)\n",
    "df['bytes_in'] = df['bytes_in'].astype(int)\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       index  Unnamed: 0   sourcetype                          endtime  \\\n",
      "12768  16640       16640   stream:tcp 2022-07-27 00:25:47.758084+00:00   \n",
      "7274    9503        9503   stream:tcp 2022-07-27 00:19:17.178540+00:00   \n",
      "7213    9399        9399  stream:http 2022-07-27 00:19:17.236152+00:00   \n",
      "7276    9507        9507  stream:http 2022-07-27 00:19:17.226262+00:00   \n",
      "7275    9505        9505   stream:tcp 2022-07-27 00:19:17.521373+00:00   \n",
      "\n",
      "                             timestamp  bytes     src_ip            src_mac  \\\n",
      "12768 2022-07-27 00:18:42.697892+00:00  66735   10.0.0.9  00:0D:3A:1A:CC:00   \n",
      "7274  2022-07-27 00:19:16.275980+00:00  83172  10.0.0.11  00:0D:3A:1A:C4:8D   \n",
      "7213  2022-07-27 00:19:17.226483+00:00   3570  10.0.0.10  00:0D:3A:10:65:C8   \n",
      "7276  2022-07-27 00:19:17.225196+00:00    821  10.0.0.10  00:0D:3A:10:65:C8   \n",
      "7275  2022-07-27 00:19:17.360957+00:00    354  10.0.0.10  00:0D:3A:10:65:C8   \n",
      "\n",
      "       src_port           connection  ...  uri_query  http_user_agent  cookie  \\\n",
      "12768     55340  168.63.129.16:32526  ...        NaN              NaN     NaN   \n",
      "7274      55286    104.71.186.56:443  ...        NaN              NaN     NaN   \n",
      "7213      49710                  NaN  ...        NaN              NaN     NaN   \n",
      "7276      49710                  NaN  ...        NaN              NaN     NaN   \n",
      "7275      55502    44.238.73.15:9997  ...        NaN              NaN     NaN   \n",
      "\n",
      "       uri_parm  message_type  query  query_type  transaction_id  \\\n",
      "12768       NaN           NaN    NaN         NaN             NaN   \n",
      "7274        NaN           NaN    NaN         NaN             NaN   \n",
      "7213        NaN           NaN    NaN         NaN             NaN   \n",
      "7276        NaN           NaN    NaN         NaN             NaN   \n",
      "7275        NaN           NaN    NaN         NaN             NaN   \n",
      "\n",
      "       epoch_timestamp epoch_endtime  \n",
      "12768       1658881122    1658881547  \n",
      "7274        1658881156    1658881157  \n",
      "7213        1658881157    1658881157  \n",
      "7276        1658881157    1658881157  \n",
      "7275        1658881157    1658881157  \n",
      "\n",
      "[5 rows x 81 columns]\n"
     ]
    }
   ],
   "source": [
    "print(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3962bb17-b59d-4530-84de-c6519aa9ce73",
   "metadata": {},
   "source": [
    "## PROCESS DATA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.13 Jupyter notebook code – Calculate the time difference between similar connections\n",
    "\n",
    "- A Save the time difference between consecutive events in a new field time_diff_sec based on the value epoch_timestamp, which is in seconds. In Python, lambda allows you to define expressions, allowing you to write simple functions with a single expression without defining them with the def keyword. In our case, we are applying an expression that calculates the time difference between the consecutive values of epoch_timestamp. apply() is used with Python lambda to execute the expression. In our case, we apply the expression after grouping by src_ip, dest_ip , and dest_port. The results of applying the expression are stored in a new column, time_diff_sec, in the same DataFrame, df."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3dab9329-140b-4aec-a761-90767cf82be3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['time_diff_sec'] = df.groupby(['src_ip', 'dest_ip', 'dest_port'])\\\n",
    "    ['epoch_timestamp'].transform(lambda x: x - x.shift(1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.14 Jupyter notebook code – Calculate standard deviation, variance and count\n",
    "\n",
    "- A Calculate the standard deviation for rows that share the same src_ip, dest_ip, and dest_portusing the values in column time_diff_sec and store the results in a new column std1\n",
    "- B Calculate the variance for rows that share the same src_ip, dest_ip, and dest_port using the values in column time_diff_sec and store the results in a new column var1\n",
    "- C Count rows that share the same src_ip, dest_ip, and dest_port using the values in column time_diff_sec and store the results in a new column count1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0cfd3ffb-23d1-4961-9306-5331f3ab6155",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>var1</th>\n",
       "      <th>std1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146495</th>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>0.080322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376303</th>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>0.080322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162267</th>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>0.080322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402800</th>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>0.080322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137725</th>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>0.080322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4332</th>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>3977.842291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4336</th>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>3977.842291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4355</th>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>3977.842291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4372</th>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>3977.842291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37880</th>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>3977.842291</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>511346 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                var1         std1\n",
       "146495  6.451613e-03     0.080322\n",
       "376303  6.451613e-03     0.080322\n",
       "162267  6.451613e-03     0.080322\n",
       "402800  6.451613e-03     0.080322\n",
       "137725  6.451613e-03     0.080322\n",
       "...              ...          ...\n",
       "4332    1.582323e+07  3977.842291\n",
       "4336    1.582323e+07  3977.842291\n",
       "4355    1.582323e+07  3977.842291\n",
       "4372    1.582323e+07  3977.842291\n",
       "37880   1.582323e+07  3977.842291\n",
       "\n",
       "[511346 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['std1'] = df.groupby(['src_ip', 'dest_ip', 'dest_port'])\\\n",
    "    ['time_diff_sec'].transform('std')\n",
    "df['var1'] = df.groupby(['src_ip', 'dest_ip', 'dest_port'])\\\n",
    "    ['time_diff_sec'].transform('var')\n",
    "df['count1'] = df.groupby(['src_ip', 'dest_ip', 'dest_port'])\\\n",
    "    ['time_diff_sec'].transform('count')\n",
    "df[['var1','std1']].sort_values(by=['std1'], ascending=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.15 Jupyter notebook code – Display selected columns in the DataFrame df\n",
    "- A Display few columns in the DataFrame df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "008c939f-f807-4972-9492-6961de30083e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>src_ip</th>\n",
       "      <th>dest_ip</th>\n",
       "      <th>dest_port</th>\n",
       "      <th>std1</th>\n",
       "      <th>var1</th>\n",
       "      <th>count1</th>\n",
       "      <th>app</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146495</th>\n",
       "      <td>10.0.0.8</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.080322</td>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>155</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376303</th>\n",
       "      <td>10.0.0.8</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.080322</td>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>155</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162267</th>\n",
       "      <td>10.0.0.8</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.080322</td>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>155</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402800</th>\n",
       "      <td>10.0.0.8</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.080322</td>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>155</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137725</th>\n",
       "      <td>10.0.0.8</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.080322</td>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>155</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4332</th>\n",
       "      <td>10.0.0.10</td>\n",
       "      <td>108.138.128.47</td>\n",
       "      <td>443</td>\n",
       "      <td>3977.842291</td>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>107</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4336</th>\n",
       "      <td>10.0.0.10</td>\n",
       "      <td>108.138.128.47</td>\n",
       "      <td>443</td>\n",
       "      <td>3977.842291</td>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>107</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4355</th>\n",
       "      <td>10.0.0.10</td>\n",
       "      <td>108.138.128.47</td>\n",
       "      <td>443</td>\n",
       "      <td>3977.842291</td>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>107</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4372</th>\n",
       "      <td>10.0.0.10</td>\n",
       "      <td>108.138.128.47</td>\n",
       "      <td>443</td>\n",
       "      <td>3977.842291</td>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>107</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37880</th>\n",
       "      <td>10.0.0.10</td>\n",
       "      <td>108.138.128.47</td>\n",
       "      <td>443</td>\n",
       "      <td>3977.842291</td>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>107</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>511346 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           src_ip         dest_ip  dest_port         std1          var1  \\\n",
       "146495   10.0.0.8  52.226.139.185        443     0.080322  6.451613e-03   \n",
       "376303   10.0.0.8  52.226.139.185        443     0.080322  6.451613e-03   \n",
       "162267   10.0.0.8  52.226.139.185        443     0.080322  6.451613e-03   \n",
       "402800   10.0.0.8  52.226.139.185        443     0.080322  6.451613e-03   \n",
       "137725   10.0.0.8  52.226.139.185        443     0.080322  6.451613e-03   \n",
       "...           ...             ...        ...          ...           ...   \n",
       "4332    10.0.0.10  108.138.128.47        443  3977.842291  1.582323e+07   \n",
       "4336    10.0.0.10  108.138.128.47        443  3977.842291  1.582323e+07   \n",
       "4355    10.0.0.10  108.138.128.47        443  3977.842291  1.582323e+07   \n",
       "4372    10.0.0.10  108.138.128.47        443  3977.842291  1.582323e+07   \n",
       "37880   10.0.0.10  108.138.128.47        443  3977.842291  1.582323e+07   \n",
       "\n",
       "        count1      app  \n",
       "146495     155  unknown  \n",
       "376303     155  unknown  \n",
       "162267     155  unknown  \n",
       "402800     155  unknown  \n",
       "137725     155  unknown  \n",
       "...        ...      ...  \n",
       "4332       107      ssl  \n",
       "4336       107      ssl  \n",
       "4355       107      ssl  \n",
       "4372       107      ssl  \n",
       "37880      107      ssl  \n",
       "\n",
       "[511346 rows x 7 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['src_ip', 'dest_ip', 'dest_port', 'std1', 'var1', 'count1', 'app']]\\\n",
    "    .sort_values(by=['std1'], ascending=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.16 Jupyter notebook code – Drop duplicates\n",
    "- A Remove the duplicate rows based on src_ip, dest_ip, and dest_port and store the result in a new DataFrame, unique_df\n",
    "- B Sort unique_df ascending based on the value of std1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0dc8f922-7566-4007-bf29-eee8e56fa022",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>src_ip</th>\n",
       "      <th>dest_ip</th>\n",
       "      <th>dest_port</th>\n",
       "      <th>std1</th>\n",
       "      <th>var1</th>\n",
       "      <th>count1</th>\n",
       "      <th>app</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>65430</th>\n",
       "      <td>10.0.0.8</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.080322</td>\n",
       "      <td>6.451613e-03</td>\n",
       "      <td>155</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4782</th>\n",
       "      <td>10.0.0.7</td>\n",
       "      <td>52.226.139.121</td>\n",
       "      <td>443</td>\n",
       "      <td>0.094701</td>\n",
       "      <td>8.968244e-03</td>\n",
       "      <td>222</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10220</th>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.277019</td>\n",
       "      <td>7.673964e-02</td>\n",
       "      <td>222</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4577</th>\n",
       "      <td>10.0.0.12</td>\n",
       "      <td>52.226.139.121</td>\n",
       "      <td>443</td>\n",
       "      <td>0.286851</td>\n",
       "      <td>8.228333e-02</td>\n",
       "      <td>170</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7051</th>\n",
       "      <td>10.0.0.12</td>\n",
       "      <td>44.238.73.15</td>\n",
       "      <td>9997</td>\n",
       "      <td>0.309736</td>\n",
       "      <td>9.593646e-02</td>\n",
       "      <td>1378</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32756</th>\n",
       "      <td>10.0.0.7</td>\n",
       "      <td>173.222.170.99</td>\n",
       "      <td>80</td>\n",
       "      <td>2627.209391</td>\n",
       "      <td>6.902229e+06</td>\n",
       "      <td>115</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24175</th>\n",
       "      <td>10.0.0.4</td>\n",
       "      <td>173.222.170.99</td>\n",
       "      <td>80</td>\n",
       "      <td>2871.318325</td>\n",
       "      <td>8.244469e+06</td>\n",
       "      <td>105</td>\n",
       "      <td>ebay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94899</th>\n",
       "      <td>10.0.0.11</td>\n",
       "      <td>192.111.4.10</td>\n",
       "      <td>443</td>\n",
       "      <td>3342.416695</td>\n",
       "      <td>1.117175e+07</td>\n",
       "      <td>168</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87408</th>\n",
       "      <td>10.0.0.10</td>\n",
       "      <td>108.138.128.122</td>\n",
       "      <td>443</td>\n",
       "      <td>3663.833032</td>\n",
       "      <td>1.342367e+07</td>\n",
       "      <td>104</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38214</th>\n",
       "      <td>10.0.0.10</td>\n",
       "      <td>108.138.128.47</td>\n",
       "      <td>443</td>\n",
       "      <td>3977.842291</td>\n",
       "      <td>1.582323e+07</td>\n",
       "      <td>107</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>584 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          src_ip          dest_ip  dest_port         std1          var1  \\\n",
       "65430   10.0.0.8   52.226.139.185        443     0.080322  6.451613e-03   \n",
       "4782    10.0.0.7   52.226.139.121        443     0.094701  8.968244e-03   \n",
       "10220   10.0.0.6   52.226.139.185        443     0.277019  7.673964e-02   \n",
       "4577   10.0.0.12   52.226.139.121        443     0.286851  8.228333e-02   \n",
       "7051   10.0.0.12     44.238.73.15       9997     0.309736  9.593646e-02   \n",
       "...          ...              ...        ...          ...           ...   \n",
       "32756   10.0.0.7   173.222.170.99         80  2627.209391  6.902229e+06   \n",
       "24175   10.0.0.4   173.222.170.99         80  2871.318325  8.244469e+06   \n",
       "94899  10.0.0.11     192.111.4.10        443  3342.416695  1.117175e+07   \n",
       "87408  10.0.0.10  108.138.128.122        443  3663.833032  1.342367e+07   \n",
       "38214  10.0.0.10   108.138.128.47        443  3977.842291  1.582323e+07   \n",
       "\n",
       "       count1      app  \n",
       "65430     155      ssl  \n",
       "4782      222  unknown  \n",
       "10220     222  unknown  \n",
       "4577      170  unknown  \n",
       "7051     1378  unknown  \n",
       "...       ...      ...  \n",
       "32756     115      NaN  \n",
       "24175     105     ebay  \n",
       "94899     168      ssl  \n",
       "87408     104      ssl  \n",
       "38214     107      ssl  \n",
       "\n",
       "[584 rows x 7 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_df = df.drop_duplicates(['src_ip', 'dest_ip', 'dest_port'])\n",
    "unique_df[['src_ip', 'dest_ip', 'dest_port', 'std1', 'var1',\\\n",
    "    'count1', 'app']].sort_values(by=['std1'], ascending=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IDENTIFY BEACONING"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.15 Jupyter notebook code – Keep rows with low standard deviation values\n",
    "\n",
    "- A Set the value of a new variable, std_threshold to 100\n",
    "- B Look for rows with std1 < std_threshold and update unique_df accordingly\n",
    "- C Display the value of specific columns after sorting unique_df in ascending order based on the value of std1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>src_ip</th>\n",
       "      <th>dest_ip</th>\n",
       "      <th>dest_port</th>\n",
       "      <th>std1</th>\n",
       "      <th>var1</th>\n",
       "      <th>count1</th>\n",
       "      <th>app</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>65430</th>\n",
       "      <td>10.0.0.8</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.080322</td>\n",
       "      <td>0.006452</td>\n",
       "      <td>155</td>\n",
       "      <td>ssl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4782</th>\n",
       "      <td>10.0.0.7</td>\n",
       "      <td>52.226.139.121</td>\n",
       "      <td>443</td>\n",
       "      <td>0.094701</td>\n",
       "      <td>0.008968</td>\n",
       "      <td>222</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10220</th>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>52.226.139.185</td>\n",
       "      <td>443</td>\n",
       "      <td>0.277019</td>\n",
       "      <td>0.076740</td>\n",
       "      <td>222</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4577</th>\n",
       "      <td>10.0.0.12</td>\n",
       "      <td>52.226.139.121</td>\n",
       "      <td>443</td>\n",
       "      <td>0.286851</td>\n",
       "      <td>0.082283</td>\n",
       "      <td>170</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7051</th>\n",
       "      <td>10.0.0.12</td>\n",
       "      <td>44.238.73.15</td>\n",
       "      <td>9997</td>\n",
       "      <td>0.309736</td>\n",
       "      <td>0.095936</td>\n",
       "      <td>1378</td>\n",
       "      <td>unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6469</th>\n",
       "      <td>10.0.0.12</td>\n",
       "      <td>169.254.169.254</td>\n",
       "      <td>80</td>\n",
       "      <td>90.116138</td>\n",
       "      <td>8120.918315</td>\n",
       "      <td>459</td>\n",
       "      <td>windows_azure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9027</th>\n",
       "      <td>10.0.0.9</td>\n",
       "      <td>169.254.169.254</td>\n",
       "      <td>80</td>\n",
       "      <td>90.371816</td>\n",
       "      <td>8167.065044</td>\n",
       "      <td>129</td>\n",
       "      <td>windows_azure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26766</th>\n",
       "      <td>10.0.0.12</td>\n",
       "      <td>208.80.154.224</td>\n",
       "      <td>443</td>\n",
       "      <td>92.376621</td>\n",
       "      <td>8533.440114</td>\n",
       "      <td>2567</td>\n",
       "      <td>wikipedia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8544</th>\n",
       "      <td>10.0.0.4</td>\n",
       "      <td>208.80.154.224</td>\n",
       "      <td>443</td>\n",
       "      <td>97.746365</td>\n",
       "      <td>9554.351840</td>\n",
       "      <td>3293</td>\n",
       "      <td>wikipedia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7220</th>\n",
       "      <td>10.0.0.8</td>\n",
       "      <td>208.80.154.224</td>\n",
       "      <td>443</td>\n",
       "      <td>98.281620</td>\n",
       "      <td>9659.276790</td>\n",
       "      <td>2632</td>\n",
       "      <td>wikipedia</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          src_ip          dest_ip  dest_port       std1         var1  count1  \\\n",
       "65430   10.0.0.8   52.226.139.185        443   0.080322     0.006452     155   \n",
       "4782    10.0.0.7   52.226.139.121        443   0.094701     0.008968     222   \n",
       "10220   10.0.0.6   52.226.139.185        443   0.277019     0.076740     222   \n",
       "4577   10.0.0.12   52.226.139.121        443   0.286851     0.082283     170   \n",
       "7051   10.0.0.12     44.238.73.15       9997   0.309736     0.095936    1378   \n",
       "...          ...              ...        ...        ...          ...     ...   \n",
       "6469   10.0.0.12  169.254.169.254         80  90.116138  8120.918315     459   \n",
       "9027    10.0.0.9  169.254.169.254         80  90.371816  8167.065044     129   \n",
       "26766  10.0.0.12   208.80.154.224        443  92.376621  8533.440114    2567   \n",
       "8544    10.0.0.4   208.80.154.224        443  97.746365  9554.351840    3293   \n",
       "7220    10.0.0.8   208.80.154.224        443  98.281620  9659.276790    2632   \n",
       "\n",
       "                 app  \n",
       "65430            ssl  \n",
       "4782         unknown  \n",
       "10220        unknown  \n",
       "4577         unknown  \n",
       "7051         unknown  \n",
       "...              ...  \n",
       "6469   windows_azure  \n",
       "9027   windows_azure  \n",
       "26766      wikipedia  \n",
       "8544       wikipedia  \n",
       "7220       wikipedia  \n",
       "\n",
       "[66 rows x 7 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "std_threshold = 100\n",
    "unique_df = unique_df.loc[unique_df['std1'] <  \\\n",
    "    std_threshold].sort_values(by=['dest_ip'], ascending=True)\n",
    "unique_df[['src_ip', 'dest_ip', 'dest_port', \\\n",
    "    'std1', 'var1', 'count1',  'app']].sort_values(by=['std1'], ascending=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.16 Jupyter notebook code – Summarize the unique destination IP addresses\n",
    "- A Drop duplicate records based on dest_ip and update unique_df accordingly\n",
    "- B Display the rows of unique_df sorted in ascending order based on dest_ip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dest_ip</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>495078</th>\n",
       "      <td>10.0.0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7243</th>\n",
       "      <td>10.0.0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222037</th>\n",
       "      <td>10.0.0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7252</th>\n",
       "      <td>10.0.0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7262</th>\n",
       "      <td>10.0.0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7268</th>\n",
       "      <td>10.0.0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7267</th>\n",
       "      <td>10.0.0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7263</th>\n",
       "      <td>10.0.0.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7208</th>\n",
       "      <td>168.63.129.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8697</th>\n",
       "      <td>169.254.169.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55152</th>\n",
       "      <td>192.111.4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26766</th>\n",
       "      <td>208.80.154.224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59308</th>\n",
       "      <td>34.125.188.180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7223</th>\n",
       "      <td>44.238.73.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4782</th>\n",
       "      <td>52.226.139.121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5335</th>\n",
       "      <td>52.226.139.180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4521</th>\n",
       "      <td>52.226.139.185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                dest_ip\n",
       "495078        10.0.0.10\n",
       "7243          10.0.0.11\n",
       "222037        10.0.0.12\n",
       "7252           10.0.0.4\n",
       "7262           10.0.0.6\n",
       "7268           10.0.0.7\n",
       "7267           10.0.0.8\n",
       "7263           10.0.0.9\n",
       "7208      168.63.129.16\n",
       "8697    169.254.169.254\n",
       "55152       192.111.4.1\n",
       "26766    208.80.154.224\n",
       "59308    34.125.188.180\n",
       "7223       44.238.73.15\n",
       "4782     52.226.139.121\n",
       "5335     52.226.139.180\n",
       "4521     52.226.139.185"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_df = unique_df.loc[unique_df['std1'] < \\\n",
    "    std_threshold].drop_duplicates(['dest_ip'])\n",
    "unique_df[['dest_ip']].sort_values(by=['dest_ip'], \\\n",
    "    ascending=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BEACONING TO 208.80.154.224"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Listing 6.19 Jupyter notebook code – IP addresses communicating with 208.80.154.224\n",
    "- A Search for events with field dest_ip set to 208.80.154.224. Group and count the output of the previous command based on the src_ip, dest_ip, dest_port, app and sourcetype."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "src_ip     dest_ip         dest_port  app        sourcetype\n",
       "10.0.0.10  208.80.154.224  80         wikipedia  stream:tcp      10\n",
       "                           443        wikipedia  stream:tcp    3591\n",
       "10.0.0.11  208.80.154.224  80         wikipedia  stream:tcp       4\n",
       "                           443        wikipedia  stream:tcp    4128\n",
       "10.0.0.12  208.80.154.224  443        wikipedia  stream:tcp    2568\n",
       "10.0.0.4   208.80.154.224  80         wikipedia  stream:tcp      14\n",
       "                           443        wikipedia  stream:tcp    3294\n",
       "10.0.0.6   208.80.154.224  80         wikipedia  stream:tcp       4\n",
       "                           443        wikipedia  stream:tcp    4069\n",
       "10.0.0.7   208.80.154.224  80         wikipedia  stream:tcp       4\n",
       "                           443        wikipedia  stream:tcp    3322\n",
       "10.0.0.8   208.80.154.224  80         wikipedia  stream:tcp       1\n",
       "                           443        wikipedia  stream:tcp    2633\n",
       "10.0.0.9   208.80.154.224  443        wikipedia  stream:tcp     900\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#pd.set_option('display.max_rows', 100)\n",
    "df_original.loc[df_original['dest_ip'] == \\\n",
    "    '208.80.154.224'].groupby(['src_ip',\\\n",
    "    'dest_ip', 'dest_port', 'app', 'sourcetype']).size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#pd.reset_option('display.max_rows')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.22 Jupyter notebook code – Search for 208.80.154.224 in events\n",
    "- A Search for events with dest_ip 208.80.154.224"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "src_ip     site                   uri_path                                                       status\n",
       "10.0.0.10  commons.wikimedia.org  /w/api.php                                                     301       1\n",
       "                                  /w/index.php                                                   301       1\n",
       "                                  /wiki/%EB%8C%80%EB%AC%B8                                       301       1\n",
       "                                  /wiki/Cifapad                                                  301       2\n",
       "                                  /wiki/Commons:Media_help                                       301       1\n",
       "                                  /wiki/Commons:Media_help/nl                                    301       1\n",
       "                                  /wiki/Faqja_kryesore                                           301       1\n",
       "                                  /wiki/File:Gnome-audio-x-generic.svg                           301       1\n",
       "                                  /wiki/Oj%C3%BAew%C3%A9_%C3%80k%E1%BB%8D%CC%81k%E1%BB%8D%CC%81  301       1\n",
       "10.0.0.11  en.wikipedia.org       /wiki/Augmentation_Research_Center                             301       1\n",
       "                                  /wiki/Douglas_Engelbart                                        301       1\n",
       "                                  /wiki/IP_address                                               301       1\n",
       "                                  /wiki/RFC_(identifier)                                         301       1\n",
       "10.0.0.4   meta.wikimedia.org     /w/index.php                                                   301       1\n",
       "                                  /wiki/Case_study_2013-02-27                                    301       1\n",
       "           species.wikimedia.org  /                                                              301       1\n",
       "                                  /w/index.php                                                   301       7\n",
       "                                  /wiki/File:Wikiquote-logo.svg                                  301       1\n",
       "                                  /wiki/Special:RecentChanges                                    301       1\n",
       "                                  /wiki/Template:Sisterprojects-yue                              301       1\n",
       "                                  /wiki/User:RLJ                                                 301       1\n",
       "10.0.0.6   de.wikipedia.org       /wiki/HTTP-Cookie                                              301       1\n",
       "           en.wikipedia.org       /wiki/SHA2                                                     301       1\n",
       "           fi.wikipedia.org       /wiki/Bannerimainonta                                          301       1\n",
       "           www.wikidata.org       /entity/Q33085608                                              301       1\n",
       "10.0.0.7   en.wikipedia.org       /wiki/1982_NBA_Finals                                          301       1\n",
       "                                  /wiki/Linfen                                                   301       1\n",
       "                                  /wiki/Xining                                                   301       1\n",
       "           www.wikidata.org       /entity/P9073                                                  301       1\n",
       "10.0.0.8   en.wikipedia.org       /wiki/OS_X_Mountain_Lion                                       301       1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_original.loc[df_original['dest_ip'] == '208.80.154.224'].\\\n",
    "    groupby(['src_ip', 'site', 'uri_path', 'status']).size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Listing 6.23 Jupyter notebook code – Plot the value of time_diff_sec for connections between 10.0.0.4 and 208.80.154.224 over port 443\n",
    "- A For specific values of src_ip, dest_ip, and dest_port in DataFrame df, sort the output based on date, set date as the index and generate a plot that shows the value of time_diff_sec over time. The plot instruction includes parameters such as the figure size, width of 25 inches and height of 5, the plot type, line, and color, orange. set(xticklabels=[]) instructs the program to plot without displaying the x-axis ticks. You can change the plot settings to match your preference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7f5d2ff8-3cec-4f27-bde4-f7c3634845e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[Text(1658870000.0, 0, ''),\n",
       "  Text(1658880000.0, 0, ''),\n",
       "  Text(1658890000.0, 0, ''),\n",
       "  Text(1658900000.0, 0, ''),\n",
       "  Text(1658910000.0, 0, ''),\n",
       "  Text(1658920000.0, 0, ''),\n",
       "  Text(1658930000.0, 0, ''),\n",
       "  Text(1658940000.0, 0, '')]]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] == \\\n",
    "    '208.80.154.224') & (df['dest_port'] == 443)].\\\n",
    "        sort_values(by=['epoch_timestamp'], ascending=True).\\\n",
    "            set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                plot(figsize=[25,5], kind='line', color='orange')\\\n",
    "                    .set(xticklabels=[])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.24 Jupyter notebook code – Plot the value of time_diff_sec for connections between 10.0.0.4 and 208.80.154.224 over port 443\n",
    "- A For specific values of src_ip, dest_ip, and dest_port in DataFrame df, sort the output based on date, set date as the index, and finally generate a histogram type of plot with a width of 25 inches and height of 5 inches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "71c50475-8017-4361-8891-c5704b8f8d0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] \\\n",
    "    == '208.80.154.224') & (df['dest_port'] == 443)].\\\n",
    "        sort_values(by=['epoch_timestamp'], ascending=True).\\\n",
    "            set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                hist(figsize=[25,5], color='orange', bins=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BEACONING TO 34.125.188.180"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.25 Jupyter notebook code – IP addresses communicating with 34.125.188.180\n",
    "- A Search for events with source column dest_ip set to 34.125.188.180, then group and count the output based on the src_ip, dest_ip, dest_port, app, and sourcetype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "src_ip    dest_ip         dest_port  app      sourcetype\n",
       "10.0.0.4  34.125.188.180  80         http     stream:tcp    755\n",
       "                                     unknown  stream:tcp    770\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_original.loc[df_original['dest_ip'] == \\\n",
    "    '34.125.188.180'].groupby(['src_ip',\\\n",
    "    'dest_ip', 'dest_port', 'app', 'sourcetype']).size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.27 Jupyter notebook code – Search for events with dest_ip 34.125.188.180\n",
    "- A Filter rows in the df_original DataFrame where the dest_ip column equals 34.125.188.180, group the filtered data by the columns src_ip, site, uri_path, and status, and then count the number of occurrences for each group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "src_ip    site            uri_path     status\n",
       "10.0.0.4  34.125.188.180  /b           200         1\n",
       "                                       404         2\n",
       "                          /cm          200       677\n",
       "                          /submit.php  200        73\n",
       "dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_original.loc[df_original['dest_ip'] == '34.125.188.180'].\\\n",
    "    groupby(['src_ip', 'site', 'uri_path', 'status']).size()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.31 Jupyter notebook code – Search for 34.125.188.180 in events with uri_path set to /submit.php or /cm\n",
    "- A Filter the df_original DataFrame for entries where the destination IP is 34.125.188.180 and the URI path is either /submit.php or /cm, group the entries by uri_path, http_method, and status, and count the number of occurrences in each group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "uri_path     http_method  status\n",
       "/cm          GET          200       677\n",
       "/submit.php  POST         200        73\n",
       "dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_original.loc[(df_original['dest_ip'] == '34.125.188.180') & \\\n",
    "    ((df_original['uri_path'] == '/submit.php') | \\\n",
    "        (df_original['uri_path'] == '/cm'))].\\\n",
    "            groupby(['uri_path', 'http_method', 'status']).size()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.33 Jupyter notebook code – Calculate the standard deviation for all values of app\n",
    "- A Filter the unique_df DataFrame for rows where the source IP is 10.0.0.4, the destination IP is 34.125.188.180, and the destination port is 80. It then groups these filtered entries by the std1 column and counts the occurrences for each unique value in std1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "std1\n",
       "28.829445    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_df.loc[(unique_df['src_ip'] == '10.0.0.4') & \\\n",
    "    (unique_df['dest_ip'] == '34.125.188.180') & \\\n",
    "        (unique_df['dest_port'] == 80)].groupby(unique_df['std1']).size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.34 Jupyter notebook code – Time difference in seconds between connections over time for all values of app\n",
    "- A Filter df for rows matching a src_ip 10.0.0.4, dest_ip 34.125.188.180, and dest_port 80, sort them by epoch_timestamp in ascending order, and then plot a line graph of the time_diff_sec values against epoch_timestamp. The x-axis labels are removed to simplify the visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[Text(1658880000.0, 0, ''),\n",
       "  Text(1658890000.0, 0, ''),\n",
       "  Text(1658900000.0, 0, ''),\n",
       "  Text(1658910000.0, 0, ''),\n",
       "  Text(1658920000.0, 0, ''),\n",
       "  Text(1658930000.0, 0, ''),\n",
       "  Text(1658940000.0, 0, '')]]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] == \\\n",
    "    '34.125.188.180') & (df['dest_port'] == 80)].\\\n",
    "        sort_values(by=['epoch_timestamp'], ascending=True).\\\n",
    "            set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                plot(figsize=[25,5], kind='line', color='orange')\\\n",
    "                    .set(xticklabels=[])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Listing 6.35 Jupyter notebook code – Calculate the standard deviation for connections with app set to http"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "app   std1     \n",
       "http  28.829445    755\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] == \\\n",
    "    '34.125.188.180')  & (df['dest_port'] == 80) & \\\n",
    "        (df['app'] == 'http')].groupby(['app', 'std1']).size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.36 Jupyter notebook code – Time difference in seconds between connections over time for app set to http"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[Text(1658880000.0, 0, ''),\n",
       "  Text(1658890000.0, 0, ''),\n",
       "  Text(1658900000.0, 0, ''),\n",
       "  Text(1658910000.0, 0, ''),\n",
       "  Text(1658920000.0, 0, ''),\n",
       "  Text(1658930000.0, 0, ''),\n",
       "  Text(1658940000.0, 0, '')]]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] == \\\n",
    "    '34.125.188.180') & (df['dest_port'] == 80) & (df['app'] == 'http')].\\\n",
    "        sort_values(by=['epoch_timestamp'], ascending=True).\\\n",
    "            set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                plot(figsize=[25,5], kind='line', color='orange')\\\n",
    "                    .set(xticklabels=[])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.39 Jupyter notebook code – Calculate the standard deviation for connections with app set to http\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "app      std1     \n",
       "unknown  28.829445    770\n",
       "dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] == \\\n",
    "    '34.125.188.180')  & (df['dest_port'] == 80) & \\\n",
    "        (df['app'] == 'unknown')].groupby(['app', 'std1']).size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.40 Jupyter notebook code – Calculating standard deviation for app set to unknown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[Text(1658884000.0, 0, ''),\n",
       "  Text(1658886000.0, 0, ''),\n",
       "  Text(1658888000.0, 0, ''),\n",
       "  Text(1658890000.0, 0, ''),\n",
       "  Text(1658892000.0, 0, ''),\n",
       "  Text(1658894000.0, 0, ''),\n",
       "  Text(1658896000.0, 0, ''),\n",
       "  Text(1658898000.0, 0, '')]]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] == \\\n",
    "    '34.125.188.180') & (df['dest_port'] == 80) & (df['app'] == 'unknown')].\\\n",
    "        sort_values(by=['epoch_timestamp'], ascending=True).\\\n",
    "            set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                plot(figsize=[25,5], kind='line', color='orange')\\\n",
    "                    .set(xticklabels=[])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.41 Jupyter notebook code – Generate a histogram showing the distribution of time_diff_sec for app set to http"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] \\\n",
    "    == '34.125.188.180') & (df['dest_port'] == 80) & \\\n",
    "        (df['app'] == 'http')].sort_values(by=['epoch_timestamp'], \\\n",
    "            ascending=True).set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                hist(figsize=[25,5], color='orange',  bins=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.42 Jupyter notebook code – Generate a histogram showing the distribution of time_diff_sec for app set to unknown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.4') & (df['dest_ip'] \\\n",
    "    == '34.125.188.180') & (df['dest_port'] == 80) & \\\n",
    "        (df['app'] == 'unknown')].sort_values(by=['epoch_timestamp'], \\\n",
    "            ascending=True).set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                hist(figsize=[25,5], color='orange', bins=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Answers to Exercise"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.45 Jupyter notebook code – Number of connections between 10.0.0.6 and 208.80.154.224"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>sourcetype</th>\n",
       "      <th>endtime</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>bytes</th>\n",
       "      <th>src_ip</th>\n",
       "      <th>src_mac</th>\n",
       "      <th>src_port</th>\n",
       "      <th>connection</th>\n",
       "      <th>client_rtt</th>\n",
       "      <th>...</th>\n",
       "      <th>ssl_cert_self_signed</th>\n",
       "      <th>form_data</th>\n",
       "      <th>uri_query</th>\n",
       "      <th>http_user_agent</th>\n",
       "      <th>cookie</th>\n",
       "      <th>uri_parm</th>\n",
       "      <th>message_type</th>\n",
       "      <th>query</th>\n",
       "      <th>query_type</th>\n",
       "      <th>transaction_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>339</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:48:10.627706Z</td>\n",
       "      <td>2022-07-27 14:48:10.128390+00:00</td>\n",
       "      <td>8962</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>53508</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>56.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>340</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:48:10.629013Z</td>\n",
       "      <td>2022-07-27 14:48:10.226906+00:00</td>\n",
       "      <td>39091</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>53509</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>49.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>358</th>\n",
       "      <td>358</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:48:08.231518Z</td>\n",
       "      <td>2022-07-27 14:48:08.082596+00:00</td>\n",
       "      <td>61793</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>53507</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>41.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359</th>\n",
       "      <td>359</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:48:08.230491Z</td>\n",
       "      <td>2022-07-27 14:48:07.996094+00:00</td>\n",
       "      <td>8966</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>53506</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>55.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>364</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:48:06.922980Z</td>\n",
       "      <td>2022-07-27 14:48:06.802735+00:00</td>\n",
       "      <td>29077</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>53505</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>44.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>666953</th>\n",
       "      <td>666953</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:14:53.060686Z</td>\n",
       "      <td>2022-07-27 14:14:52.836971+00:00</td>\n",
       "      <td>17041</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>51183</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>72.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>666969</th>\n",
       "      <td>666969</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:14:51.706012Z</td>\n",
       "      <td>2022-07-27 14:14:51.374380+00:00</td>\n",
       "      <td>28801</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>51181</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>62.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>666970</th>\n",
       "      <td>666970</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:14:51.704724Z</td>\n",
       "      <td>2022-07-27 14:14:51.242333+00:00</td>\n",
       "      <td>11090</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>51180</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>11127.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>666971</th>\n",
       "      <td>666971</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:14:51.156840Z</td>\n",
       "      <td>2022-07-27 14:14:51.030836+00:00</td>\n",
       "      <td>27827</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>51179</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>55.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>666972</th>\n",
       "      <td>666972</td>\n",
       "      <td>stream:tcp</td>\n",
       "      <td>2022-07-27T14:14:51.155698Z</td>\n",
       "      <td>2022-07-27 14:14:50.954864+00:00</td>\n",
       "      <td>9315</td>\n",
       "      <td>10.0.0.6</td>\n",
       "      <td>00:0D:3A:1A:CF:34</td>\n",
       "      <td>51178</td>\n",
       "      <td>208.80.154.224:443</td>\n",
       "      <td>54.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4077 rows × 78 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0  sourcetype                      endtime  \\\n",
       "339            339  stream:tcp  2022-07-27T14:48:10.627706Z   \n",
       "340            340  stream:tcp  2022-07-27T14:48:10.629013Z   \n",
       "358            358  stream:tcp  2022-07-27T14:48:08.231518Z   \n",
       "359            359  stream:tcp  2022-07-27T14:48:08.230491Z   \n",
       "364            364  stream:tcp  2022-07-27T14:48:06.922980Z   \n",
       "...            ...         ...                          ...   \n",
       "666953      666953  stream:tcp  2022-07-27T14:14:53.060686Z   \n",
       "666969      666969  stream:tcp  2022-07-27T14:14:51.706012Z   \n",
       "666970      666970  stream:tcp  2022-07-27T14:14:51.704724Z   \n",
       "666971      666971  stream:tcp  2022-07-27T14:14:51.156840Z   \n",
       "666972      666972  stream:tcp  2022-07-27T14:14:51.155698Z   \n",
       "\n",
       "                               timestamp  bytes    src_ip            src_mac  \\\n",
       "339     2022-07-27 14:48:10.128390+00:00   8962  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "340     2022-07-27 14:48:10.226906+00:00  39091  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "358     2022-07-27 14:48:08.082596+00:00  61793  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "359     2022-07-27 14:48:07.996094+00:00   8966  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "364     2022-07-27 14:48:06.802735+00:00  29077  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "...                                  ...    ...       ...                ...   \n",
       "666953  2022-07-27 14:14:52.836971+00:00  17041  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "666969  2022-07-27 14:14:51.374380+00:00  28801  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "666970  2022-07-27 14:14:51.242333+00:00  11090  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "666971  2022-07-27 14:14:51.030836+00:00  27827  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "666972  2022-07-27 14:14:50.954864+00:00   9315  10.0.0.6  00:0D:3A:1A:CF:34   \n",
       "\n",
       "        src_port          connection  client_rtt  ...  ssl_cert_self_signed  \\\n",
       "339        53508  208.80.154.224:443        56.0  ...                   NaN   \n",
       "340        53509  208.80.154.224:443        49.0  ...                   NaN   \n",
       "358        53507  208.80.154.224:443        41.0  ...                   NaN   \n",
       "359        53506  208.80.154.224:443        55.0  ...                   NaN   \n",
       "364        53505  208.80.154.224:443        44.0  ...                   NaN   \n",
       "...          ...                 ...         ...  ...                   ...   \n",
       "666953     51183  208.80.154.224:443        72.0  ...                   NaN   \n",
       "666969     51181  208.80.154.224:443        62.0  ...                   NaN   \n",
       "666970     51180  208.80.154.224:443     11127.0  ...                   NaN   \n",
       "666971     51179  208.80.154.224:443        55.0  ...                   NaN   \n",
       "666972     51178  208.80.154.224:443        54.0  ...                   NaN   \n",
       "\n",
       "        form_data  uri_query  http_user_agent  cookie  uri_parm  message_type  \\\n",
       "339           NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "340           NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "358           NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "359           NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "364           NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "...           ...        ...              ...     ...       ...           ...   \n",
       "666953        NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "666969        NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "666970        NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "666971        NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "666972        NaN        NaN              NaN     NaN       NaN           NaN   \n",
       "\n",
       "        query query_type  transaction_id  \n",
       "339       NaN        NaN             NaN  \n",
       "340       NaN        NaN             NaN  \n",
       "358       NaN        NaN             NaN  \n",
       "359       NaN        NaN             NaN  \n",
       "364       NaN        NaN             NaN  \n",
       "...       ...        ...             ...  \n",
       "666953    NaN        NaN             NaN  \n",
       "666969    NaN        NaN             NaN  \n",
       "666970    NaN        NaN             NaN  \n",
       "666971    NaN        NaN             NaN  \n",
       "666972    NaN        NaN             NaN  \n",
       "\n",
       "[4077 rows x 78 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_original[(df_original['src_ip'] == '10.0.0.6') & \\\n",
    "    (df_original['dest_ip'] == '208.80.154.224')]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.46 Jupyter notebook code – Calcualte the standard deviation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "std1       var1       \n",
       "78.269678  6126.142499    4069\n",
       "dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.6') & (df['dest_ip'] == \\\n",
    "    '208.80.154.224')].groupby(['std1', 'var1']).size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.47 Jupyter notebook code – Time difference between connections over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[Text(1658870000.0, 0, ''),\n",
       "  Text(1658880000.0, 0, ''),\n",
       "  Text(1658890000.0, 0, ''),\n",
       "  Text(1658900000.0, 0, ''),\n",
       "  Text(1658910000.0, 0, ''),\n",
       "  Text(1658920000.0, 0, ''),\n",
       "  Text(1658930000.0, 0, ''),\n",
       "  Text(1658940000.0, 0, '')]]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.6') & (df['dest_ip'] == \\\n",
    "    '208.80.154.224')].\\\n",
    "        sort_values(by=['epoch_timestamp'], ascending=True).\\\n",
    "            set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                plot(figsize=[25,5], kind='line', color='orange')\\\n",
    "                    .set(xticklabels=[])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Listing 6.48 Jupyter notebook code – Distribution of the time difference between connections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc[(df['src_ip'] == '10.0.0.6') & (df['dest_ip'] \\\n",
    "    == '208.80.154.224') \\\n",
    "        ].sort_values(by=['epoch_timestamp'], \\\n",
    "            ascending=True).set_index('epoch_timestamp')['time_diff_sec'].\\\n",
    "                hist(figsize=[25,5], color='orange', bins=50)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
